JRuby vs Rails: What are the differences?
JRuby: A high performance, stable, fully threaded Java implementation of the Ruby programming language. JRuby is the effort to recreate the Ruby (http://www.ruby-lang.org) interpreter in Java. The Java version is tightly integrated with Java to allow both to script any Java class and to embed the interpreter into any Java application. See the docs directory for more information; Rails: Web development that doesn't hurt. Rails is a web-application framework that includes everything needed to create database-backed web applications according to the Model-View-Controller (MVC) pattern.
JRuby belongs to "Languages" category of the tech stack, while Rails can be primarily classified under "Frameworks (Full Stack)".
"Java" is the primary reason why developers consider JRuby over the competitors, whereas "Rapid development" was stated as the key factor in picking Rails.
JRuby and Rails are both open source tools. It seems that Rails with 43.6K GitHub stars and 17.5K forks on GitHub has more adoption than JRuby with 3.32K GitHub stars and 829 GitHub forks.
Airbnb, Twitter, and Instacart are some of the popular companies that use Rails, whereas JRuby is used by Groupon, Soundcloud, and esa. Rails has a broader approval, being mentioned in 2322 company stacks & 798 developers stacks; compared to JRuby, which is listed in 13 company stacks and 4 developer stacks.
What is JRuby?
What is Rails?
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By mid-2015, around the time of the Series E, the Digital department at WeWork had grown to more than 40 people to support the company’s growing product needs.
By then, they’d migrated the main website off of WordPress to Ruby on Rails, and a combination React, Angular, and jQuery, though there were efforts to move entirely to React for the front-end.
The backend was structured around a microservices architecture built partially in Node.js, along with a combination of Ruby, Python, Bash, and Go. Swift/Objective-C and Java powered the mobile apps.
These technologies power the listings on the website, as well as various internal tools, like community manager dashboards as well as RFID hardware for access management.
When starting a new company and building a new product w/ limited engineering we chose to optimize for expertise and rapid development, landing on Rails API, w/ AngularJS on the front.
The reality is that we're building a CRUD app, so we considered going w/ vanilla Rails MVC to optimize velocity early on (it may not be sexy, but it gets the job done). Instead, we opted to split the codebase to allow for a richer front-end experience, focus on skill specificity when hiring, and give us the flexibility to be consumed by multiple clients in the future.
We also considered .NET core or Node.js for the API layer, and React on the front-end, but our experiences dealing with mature Node APIs and the rapid-fire changes that comes with state management in React-land put us off, given our level of experience with those tools.
We're using GitHub and Trello to track issues and projects, and a plethora of other tools to help the operational team, like Zapier, MailChimp, Google Drive with some basic Vue.js & HTML5 apps for smaller internal-facing web projects.
StackShare Feed is built entirely with React, Glamorous, and Apollo. One of our objectives with the public launch of the Feed was to enable a Server-side rendered (SSR) experience for our organic search traffic. When you visit the StackShare Feed, and you aren't logged in, you are delivered the Trending feed experience. We use an in-house Node.js rendering microservice to generate this HTML. This microservice needs to run and serve requests independent of our Rails web app. Up until recently, we had a mono-repo with our Rails and React code living happily together and all served from the same web process. In order to deploy our SSR app into a Heroku environment, we needed to split out our front-end application into a separate repo in GitHub. The driving factor in this decision was mostly due to limitations imposed by Heroku specifically with how processes can't communicate with each other. A new SSR app was created in Heroku and linked directly to the frontend repo so it stays in-sync with changes.
Related to this, we need a way to "deploy" our frontend changes to various server environments without building & releasing the entire Ruby application. We built a hybrid Amazon S3 Amazon CloudFront solution to host our Webpack bundles. A new CircleCI script builds the bundles and uploads them to S3. The final step in our rollout is to update some keys in Redis so our Rails app knows which bundles to serve. The result of these efforts were significant. Our frontend team now moves independently of our backend team, our build & release process takes only a few minutes, we are now using an edge CDN to serve JS assets, and we have pre-rendered React pages!
#StackDecisionsLaunch #SSR #Microservices #FrontEndRepoSplit
Back in 2014, I was given an opportunity to re-architect SmartZip Analytics platform, and flagship product: SmartTargeting. This is a SaaS software helping real estate professionals keeping up with their prospects and leads in a given neighborhood/territory, finding out (thanks to predictive analytics) who's the most likely to list/sell their home, and running cross-channel marketing automation against them: direct mail, online ads, email... The company also does provide Data APIs to Enterprise customers.
I had inherited years and years of technical debt and I knew things had to change radically. The first enabler to this was to make use of the cloud and go with AWS, so we would stop re-inventing the wheel, and build around managed/scalable services.
For the SaaS product, we kept on working with Rails as this was what my team had the most knowledge in. We've however broken up the monolith and decoupled the front-end application from the backend thanks to the use of Rails API so we'd get independently scalable micro-services from now on.
Our various applications could now be deployed using AWS Elastic Beanstalk so we wouldn't waste any more efforts writing time-consuming Capistrano deployment scripts for instance. Combined with Docker so our application would run within its own container, independently from the underlying host configuration.
Storage-wise, we went with Amazon S3 and ditched any pre-existing local or network storage people used to deal with in our legacy systems. On the database side: Amazon RDS / MySQL initially. Ultimately migrated to Amazon RDS for Aurora / MySQL when it got released. Once again, here you need a managed service your cloud provider handles for you.
Future improvements / technology decisions included:
Caching: Amazon ElastiCache / Memcached CDN: Amazon CloudFront Systems Integration: Segment / Zapier Data-warehousing: Amazon Redshift BI: Amazon Quicksight / Superset Search: Elasticsearch / Amazon Elasticsearch Service / Algolia Monitoring: New Relic
As our usage grows, patterns changed, and/or our business needs evolved, my role as Engineering Manager then Director of Engineering was also to ensure my team kept on learning and innovating, while delivering on business value.
One of these innovations was to get ourselves into Serverless : Adopting AWS Lambda was a big step forward. At the time, only available for Node.js (Not Ruby ) but a great way to handle cost efficiency, unpredictable traffic, sudden bursts of traffic... Ultimately you want the whole chain of services involved in a call to be serverless, and that's when we've started leveraging Amazon DynamoDB on these projects so they'd be fully scalable.